Sentence examples for fitting a matrix of from inspiring English sources

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They are based on fitting a matrix of individual SiPMs responses by an analytical function F x,y).

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Today's news from Prague fits into a matrix of circumstantial evidence that is emerging on the question of Iraqi support or contact with terrorist groups, but none of it directly connects Saddam Hussein to the events of Sept. 11.

As implemented in Datamonkey, REL fits a 3×3 matrix of dN and dS rates, thus allowing dS and dN to vary across sites independently.

Sex and batch were considered as fixed effects, and genetic co-variances among samples were considered by fitting a kinship matrix derived from genotypes of whole-genome SNP markers as y ∼ sex + batch + g + G, where y is a trait, G is kinship estimated based on genome-wide SNP data, and g is the genotype at a query SNP marker.

The SECS method involves setting up a matrix of current elements, fitting a geomagnetic model function, with the currents as linear output parameters, to known geomagnetic measurements at selected observatories in this region, using any decomposition inversion technique.

Also, fitting a pedigree-based relationship matrix (the A matrix) and a genome-based relationship matrix (the G matrix) together can give a higher predictive correlation than when only one matrix was fitted (Crossa et al. 2010).

The most dominant substitution matrix in the archaea dataset is the RtREV matrix (33%) with the WAG (29%) matrix close behind with the rest of the genes fitting a selection of other models.

First by fitting a linear model of the data to experimental design matrix and then by calculating Bayesian statistics.

"Enmeshed in a matrix of compromised morality".

Next was a "progressive matrices" test, which involved choosing a visual pattern that matched a matrix of other patterns.

This error term consists of a matrix of expected trait covariances calculated using the maximum likelihood estimate of lambda, a multiplier of the off-diagonal elements of a phylogenetic variance covariance matrix that best fits the data.

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